Search Results (2,767)

The rapid growth of electric vehicles (EVs) has significantly increased the demand for charging infrastructure, posing a challenge in balancing charging demand and infrastructure supply. The development of battery swapping and charging stations (BSCSs) is crucial for addressing these challenges and serves as a fundamental pillar for the sustainable advancement of EVs. This study develops a bi-level optimization model for the location and route planning of BSCSs. The upper-level model optimizes station locations to minimize total cost and service delay, while the lower-level model optimizes driver travel routes to minimize total time. An updated Non-Dominated Sorting Genetic Algorithm (UNSGA) is applied to enhance solution efficiency. The experimental results show that the bi-level model outperforms the single-level model, reducing total cost by 1.5% and travel time by 6.6%. Compared to other algorithms, the UNSGA achieves 9.43% and 8.23% lower costs than MOPSO and MOSA, respectively. Furthermore, BSCSs, despite 15.42% higher construction costs, reduce driver travel time by 22.43% and waiting time by 71.19%, highlighting their operational advantages. The bi-level optimization method provides more cost-effective decision support for EV infrastructure investors, enabling them to adapt to dynamic drivers’ needs and optimize resource allocation. Full article

This study investigates the economic viability of a new composting station dedicated to the recycling of date palm by-products. A field experiential analysis was performed in the Figuig Oasis (Morocco), providing the first evidence on the agronomic quality of the compost. The compost produced from date palm by-product was compared to cattle manure and unamended soil and can be considered as a good-quality amendment, demonstrating its ability to enhance soil fertility. Second, a socio-economic survey was conducted to explore farmers’ perceptions and adoption of sustainable agricultural practices. A total of 201 farmers out of 450 farmers registered in Figuig’s municipal administration were surveyed. In terms of fertilisation, farmers preferred locally produced organic fertiliser when available in order to improve soil organic matter content and reduce dependence on chemical inputs. The selling price for the compost was set at 0.14 EUR/kg to reflect the current market price for compost and the willingness of about 38% of the farmers surveyed to buy it. Third, a detailed cost/benefit analysis was performed, with a breakdown of the station’s operational and investment expenses. This illustrates the minimum scale needed to generate a viable business model. Financial projections show that increasing production capacity from 350 tonnes/year to 3500 tonnes/year reduces unit production costs while increasing profits. As illustrated by the application of the Ecocanvas framework, the socio-economic analysis reveals the potential to generate positive environmental, economic, and social impacts, as the circular approach could be replicable and scalable in similar oases agro ecosystems. Full article

The spatiotemporal uneven distribution of water resources conflicts sharply with human demands, with pumping stations facing efficiency decline due to aging infrastructure and complex hydraulic interactions. This study employs numerical simulation to investigate operational mechanisms in a parallel pump system at the Yanhuanding Yanghuang Cascade Pumping Station. Using ANSYS Fluent 2024 R1 and the SST k-ω turbulence model, we demonstrate that variable-speed control expands the adjustable flow range to 1.17–1.26 m³/s while maintaining system efficiency at 83–84% under head differences of 77.8–79.8 m. Critically, energy losses (δH) at the 90° outlet pipe junction escalate from 3.8% to 18.2% of total energy with increasing flow, while Q-criterion vortex analysis reveals a 63% vortex area reduction at lower speeds. Furthermore, a dual-mode energy dissipation mechanism was identified: at 0.90n₀ speed, turbulent kinetic energy surges by 115% with minimal dissipation change, indicating large-scale vortex dominance, whereas at 0.80n₀, turbulent dissipation rate increases drastically by 39%, signifying a shift to small-scale viscous dissipation. The novelty of this work lies in the first systematic quantification of junction energy losses and the revelation of turbulent energy transformation mechanisms in parallel pump systems. These findings provide a physics-based foundation for optimizing energy efficiency in high-lift cascade pumping stations. Full article

Ionospheric scintillation represents a disturbance phenomenon induced by irregular electron density variations, predominantly occurring in equatorial, auroral, and polar regions, thereby posing significant threats to Global Navigation Satellite Systems (GNSS) performance. Polar regions in particular confront distinctive challenges, including the sparse deployment of dedicated ionospheric scintillation monitoring receiver (ISMR) equipment, the limited availability of strong scintillation samples, severely imbalanced training datasets, and the insufficient sensitivity of conventional Deep Neural Networks (DNNs) to intense scintillation events. To address these challenges, this study proposes a modeling framework that integrates residual neural networks (ResNet) with the Synthetic Minority Over-sampling Technique for Regression with Gaussian Noise (SMOGN). The proposed model incorporates multi-source disturbance features to accurately estimate phase scintillation indices (${\sigma }_{\phi }$) in polar regions. The methodology was implemented and validated across multiple polar observation stations in Canada. Shapley Additive Explanations (SHAP) interpretability analysis reveals that the rate of total electron content index (ROTI) features contribute up to 64.09% of the predictive weight. The experimental results demonstrate a substantial performance enhancement compared with conventional DNN models, with root mean square error (RMSE) values ranging from 0.0078 to 0.038 for daytime samples in 2024, and an average coefficient of determination (R²) consistently exceeding 0.89. The coefficient of determination for the Pseudo-Random Noise (PRN) path estimation results can reach 0.91. The model has good estimation results at different latitudes and is able to accurately capture the distribution characteristics of the local strong scintillation structures and their evolution patterns. Full article

High-frequency wind variability plays a critical role in understanding air–sea interactions. In this study, we evaluate the performance of ERA5 reanalysis in capturing fine-scale wind variability and its impact on wind stress estimates using half-hourly observations collected from a coastal island station. Spectral analysis shows that ERA5 significantly underestimates kinetic energy at subdaily frequencies. To quantify the consequences of this spectral deficiency, we calculate subdaily wind kinetic energy. ERA5 consistently shows lower subdaily energy compared to observations. Using both two wind stress bulk formulas, we further estimate the contribution of subdaily wind variability to daily wind stress. Our results show that subdaily fluctuations contribute a considerable part of total wind stress in observations, while ERA5 systematically underestimates this contribution (often large than 20%) across all ranges of daily-mean wind speeds. These findings highlight the importance of resolving high-frequency wind variability in studies of air–sea fluxes and upper-ocean dynamics. Full article

Storm Daniel is arguably one of the most severe Mediterranean tropical-like cyclones (medicanes) ever recorded. Greece was one of the most affected areas, especially the central part of the country. The extreme precipitation that was observed along with the subsequent extensive flooding was considered a critical challenge to validate the regional version of the ICON (Icosahedral Non-Hydrostatic) numerical weather prediction (NWP) model. From a methodological standpoint, the short-range nature of the model was realized with 48 h runs over a sequence of cases that covered the storm period. The development of the medicane was highlighted via the tracking of the minimum mean sea level pressure (MSLP) in reference to the corresponding analysis of the European Center for Medium-Range Weather Forecasts (ECMWF). In a similar fashion, snapshots regarding the 500 hPa geopotential associated with the 850 hPa temperature were addressed at the 24th forecast hour of the model runs. Although the model’s performance over the four most affected synoptic stations of the Hellenic National Meteorological Service (HNMS) was mixed, the overall accumulated forecasted precipitation was in very good agreement with the corresponding total value of the observations over all the available synoptic stations. Full article

Riverbank erosion poses a significant threat to livelihoods and infrastructure in the Vietnamese Mekong Delta (VMD), necessitating innovative and sustainable solutions. This study explores the use of old tyres as a material for embankment construction to stabilize riverbanks, combining physical reinforcement with bioengineering techniques. A pilot project was conducted in Dinh My commune, An Giang Province, where an embankment was constructed using old tyres, geotextile, riprap, and vegetation. Field measurements using the Leica TS02 Plus Total Station and Finite Element Method (FEM) modeling were employed to assess the embankment’s performance. Results indicate that the embankment effectively stabilized the riverbank, with a maximum displacement of 18 mm observed after one year. The FEM predictions closely aligned with the measured data, achieving an accuracy of 68% or higher, validating the model’s accuracy. The integration of vegetation further enhanced stability, demonstrating the potential of this approach as a sustainable and cost-effective solution for riverbank protection. This study highlights the dual benefits of erosion control and waste management, offering a replicable strategy for addressing riverbank erosion across deltaic and lowland regions. The pilot offers a scalable model for climate-resilient infrastructure in deltaic regions globally, linking erosion control with circular economy strategies. Full article

With the rapid rise in electric vehicle (EV) adoption, the deployment of EV charging infrastructure—particularly fast-charging stations—has expanded significantly to meet growing energy demands. While fast charging offers the advantage of reduced charging time and improved user convenience, it imposes considerable stress on existing power distribution systems due to its high power and current requirements. This study investigated the impact of EV fast charging on power quality within Thailand’s distribution network, emphasizing compliance with accepted standards such as IEEE Std 519-2014. We developed a control-oriented EV-charging station model in power systems computer-aided design and electromagnetic transients, including DC (PSCAD/EMTDC), which integrates grid-side vector control with DC fast-charging (CC/CV) behavior. Active/reactive power setpoints were mapped onto $dq$ current references via Park’s transformation and regulated by proportional integral (PI) controllers with sinusoidal pulse-width modulation (SPWM) to command the voltage source converter (VSC) switches. The model enabled dynamic studies across battery state-of-charge and staggered charging schedules while monitoring voltage, current, and total harmonic distortion (THD) at both transformer sides, charger AC terminals, and DC adapters. Across all scenarios, the developed control achieved grid-current THDi of <5% and voltage THD of <1.5%, thereby meeting IEEE 519-2014 limits. These quantitative results show that the proposed, implementation-ready approach maintains acceptable power quality under diverse fast-charging patterns and provides actionable guidance for planning and scaling EV fast-charging infrastructure in Thailand’s urban networks. Full article

This research examines in detail the behavior of the Equatorial Ionization Anomaly (EIA) during a severe geomagnetic storm that occurred on 10–11 October 2024. The global data of Total Electron Content (TEC) represented by relative deviation, giving information about the variations compared to quiet conditions, were used. The main attention is paid to the appearance of an additional “fountain effect” under the action of disturbed dynamo currents and the vertical drift of the ionospheric plasma caused by them. The results show that the area in which a positive response (increase) of TEC is observed occurs in an area corresponding to local time around 18–20 h (longitude around 60 °W) at magnetic latitudes ±30° and during the storm shifts westward to around 180 °W. The westward drift of the storm-induced “fountain effect” is moving at a speed much slower than the Earth’s rotation speed. As a result, the area of positive TEC response (vertical upward drift) and the area of negative response (vertical downward drift) are localized in both nighttime and daytime conditions. In this investigation, an example of a very similar geomagnetic storm registered on 25 September 1998 is given for comparison, in which a similar stationing of the storm-induced EIA was observed at longitudes around 180 °E. Full article

Nuclear power continues to be a great promise in the green revolution, as it is a cost-effective, low-emission, and safer alternative to fossil fuels that is capable of continuous operation. A preliminary design evaluation is presented for a submersible nuclear power station capable of operating under its own power during emergencies and routine maintenance. Because it is stationed at sea, it offers a resilient solution to natural disasters such as earthquakes and tsunamis, giving it the capability to disengage and sail to deeper waters in less than a half of an hour. In the present evaluation, the hull dimensions of a very large existing submarine and the turbomachinery layout of a Pebble Bed Modular Reactor cycle were used as baselines. The conceptual design of the submersible nuclear power station includes reactor and turbomachinery integration, preliminary sizing (4 pressure hull design; total length of 57.74 m), and propulsion system analysis, demonstrating the technical viability of the proposed submersible power station. Full article

Sixth-generation (6G) communication systems, with ultra-wide bands, energy-autonomous end nodes, and dense connectivity, challenge existing network designs. Optimizing time resources with energy harvesting, backscatter communication, and relays is essential to maximize the total bit rate in multi-user symbiotic radio networks (SRNs) with blocked direct paths. The literature lacks a unified optimization treatment that explicitly accounts for imperfect successive interference cancellation (SIC). This study addresses this gap by proposing the first optimization framework to maximize total bit rate for energy-harvesting TDMA/PD–NOMA-based multi-cluster and relay-assisted peer-assisted SR networks. The two-phase architecture defines a tractable constrained optimization problem that jointly adjusts cluster-specific time slots ($\mathit{\tau }$ and $\lambda$). Incorporating QoS, signal power, and reflection coefficient constraints, it provides a compact formulation and numerical solutions for both perfect and imperfect SIC. Detailed simulations performed under typical 6G power levels, bandwidths, and energy-harvesting efficiencies demonstrate graphically that imperfect SIC significantly limits total throughput due to residual interference, while perfect SIC completely eliminates this ceiling under the same conditions, providing a significant capacity advantage. Furthermore, the gap between the two scenarios rapidly closes with increasing relay time margin. The findings demonstrate that network capacity is primarily determined by the triad of base station output power, channel noise, and SIC accuracy, and that the proposed framework achieves strong performance across the explored parameter space. Full article

Streamflow generated from snowmelt is important, and changing, in snow dominated regions of the world. We used a recently developed technique to estimate the start and end of snowmelt streamflow for 39 gauging stations across Colorado and determined the 40-year trends from 1981 to 2020. Most watersheds showed a trend towards an earlier start (34 watersheds) or end (29 watersheds) of snowmelt streamflow, but the mean of the start and end dates showed mixed trends (earlier in 12 watersheds and later in 20). We determined the correlation between these streamflow snowmelt trends and terrain parameters plus trends in canopy cover, winter precipitation, peak snow water equivalent, and melt-period temperature. There were some significant correlations, primarily for total annual streamflow and the timing and volume of the end of snowmelt streamflow contribution to winter precipitation (decreasing), minimum temperature (warming), and slope (negatively). Higher elevation watersheds tend to be steeper, less snow has been observed at higher elevations, and the snowpack is melting sooner. Snowmelt streamflow trends are partially explained by climate trends and watershed characteristics. Full article

As the electrification reform accelerates in ports worldwide, the application of electric tugboats is becoming more widely applied, posing a challenge in the balance between working arrangement and energy replenishment, especially when the shore energy replenishment facilities are limited. Aligning with the emerging trends of port electrification, unmanned operations, and intelligentization, this paper investigates unmanned electric tugboat scheduling considering battery-swapping operations that combine the assignment of tasks to the working periods of tugboats, the allocation of battery-swapping operations to the shore battery-swapping stations, and the sequencing of operations at each station. The problem is formulated into a mixed-integer linear programming to minimize the total completion time of the battery-swapping operations. A logic-based Benders decomposition method is proposed that decomposes the problem into a master problem and a subproblem. The master problem relaxes the sequencing constraints and solves the assignment of tasks to tugboats and the allocation of battery-swapping operations to stations. The SP, based on the solution to the master problem, determines the sequencing of battery-swapping operations at each station. Considering the interdependence of swapping operations of each tugboat that might be allocated to different stations, a dispatching heuristic is designed to efficiently obtain high-quality sequences for the stations. Numerical experiments are conducted based on 80 randomly-generated instances with up to 100 tasks, ten tugboats, and six battery-swapping stations. The results demonstrate that LBBD is capable of solving all 80 instances, whereas the commercial solver CPLEX fails to solve those with 80 or more tasks. Moreover, the average computational time of CPLEX on the instances it can solve is 241.32 s, nearly 32 times that of LBBD (7.57 s). This clearly indicates that LBBD significantly outperforms CPLEX in terms of both computational capacity and efficiency. Further analyses show that the increase in the number of tugboats will significantly shorten the makespan and make ETSBS easier to solve, while the increase in the number of battery-swapping stations makes the problem more challenging with longer computational time. Full article

Evacuation in public places under emergency situations represents a significant area of management research. With the rapid development of the railway industry, the evacuation of railway stations has gradually attracted attention. This article employs the minimization of congestion degree and total evacuation time as primary objectives. In addition, the psychological behavior of individuals and the impact of congestion are sufficiently considered. Moreover, an adaptive Cauchy mutation operator is adopted for flexible population diversity. As a result, a multi-objective optimization model for the evacuation paths is established, with an improved adaptive quantum ant colony algorithm, and a comparison between the model based on adaptive quantum ant colony algorithm and the traditional ant colony model is made. Full article

Monitoring rainfall is essential to understanding hydrological processes, managing water resources, and mitigating drought and flood risks. Many regions, particularly in developing countries, have sparse rain gauge networks, which limit spatial coverage and result in inaccurate rainfall estimates. By combining remote sensing data with rain gauge measurements, rainfall estimates can be improved, and spatial coverage can be enhanced. Remote sensing techniques provide a valuable resource for supplementing and enhancing rainfall monitoring in such areas. This study leverages Global Precipitation Measurement (GPM) satellite data to enhance rainfall estimation in White Nile State, Sudan, where only two rain gauge stations are operational and the state’s total area is 39.600 km². GPM data, well-known for its high temporal and spatial resolution, offers a promising alternative to mitigate the limitations of sparse ground-based networks. The study integrates GPM satellite data with ground-based measurements through statistical and geostatistical techniques, as well as validation, to improve rainfall accuracy. The results show that, on average, GPM data and rain gauge measurements exhibit a strong correlation of 0.87, with an annual RMSE of 10.23 mm and an AME of 8.25 mm. These findings demonstrate that GPM data effectively complements traditional rain gauge observations by accurately capturing spatial rainfall distributions and extreme precipitation events. The findings underscore the potential of remote sensing to provide reliable rainfall information in data-scarce regions, contributing to better water resource management and disaster risk reduction strategies. Full article